Lone Wolf Unleashed - avoid exhaustion, reclaim your time using tools, systems and AI

Most AI agent content is hype. This isn’t.I’m Mike, host of Lone Wolf Unleashed. This week I walk you through how I implemented my first AI agent team using Paperclip — an open-source multi-agent platform — and more importantly, the methodical approach that made the result controllable rather than chaotic.The short version: I started with a target operating model in Obsidian, not with the tool. People, process, technology, on a page. I handed the architecture to Claude, spun up a “CEO agent” in Paperclip, and let it form a team — CTO, business analyst, content writer, marketing manager, clips publisher — that now runs my content pipeline from Asana through Descript, SharePoint and into Metricool.Architecture before automation. Human-in-the-loop, non-negotiable. You’re still the master of your business.Listen to hear me walk you through it.Chapters00:00 First AI agent team, implemented00:30 Why Paperclip (and going from local to cloud)01:18 Starting with a target operating model in Obsidian02:03 Handing the architecture to Claude02:22 The CEO agent spawns the team03:40 The content workflow: Asana → Descript → SharePoint → Paperclip → Metricool05:04 Matching agents to models: Opus, Sonnet, Haiku05:56 Routines instead of manual triggers06:40 What took the time (spoiler: it wasn’t the agents)07:34 Human-in-the-loop and run history09:10 You are the master of your business10:54 The 80/20 rule for phase-one buildsResources: lonewolfunleashed.com/resourcesMentioned in this episode:You might also like...Check out the "Websites Made Simple" podcast with Holly Christie at https://websitesmadesimple.co.uk/This podcast is part of the Podknows Podcasting ICN Network

Are your AI tools burning through tokens faster than ever? You're not alone — and in this episode I'm sharing the framework that's changed how I manage knowledge and query AI at scale.I'm Mike from Lone Wolf Unleashed — I help solo founders build business systems so they can switch off sooner and live larger. Today I'm walking through Andrej Karpathy's wiki methodology, how to implement it in Obsidian, and why it reduces AI token consumption by up to 85% compared to traditional approaches.I also cover how I've applied this directly to Lone Wolf Unleashed — building a target operating model, setting up agent teams in Paperclip, and designing a content production architecture that closes the gap between production and distribution for a solo operator.If you're hitting your AI limits, spending too much on token-heavy workflows, or just looking for a smarter way to manage your business knowledge — this one's for you.──────────────────────────────Chapters──────────────────────────────00:00 — Introduction: Token limits and why this matters for solo founders00:43 — How Andrej Karpathy's wiki methodology works02:50 — Setting up a wiki ingest workflow in Obsidian03:33 — Why the wiki is 80–85% more token efficient04:38 — Visualising knowledge connections with Obsidian's graph view05:56 — Replacing a team of analysts as a solo operator06:43 — Target operating models and the 5Ps framework07:50 — Introducing Paperclip and automated content production10:13 — Building an AI Business Analyst assistant13:00 — What this means for your business and your life14:21 — Resources and wrap-up──────────────────────────────RESOURCES──────────────────────────────Wiki resources and setup guide: https://lonewolfunleashed.com/resources──────────────────────────────CONNECT──────────────────────────────Website: https://lonewolfunleashed.comEmail Mike: [email protected] in this episode:You might also like...Check out the "Websites Made Simple" podcast with Holly Christie at https://websitesmadesimple.co.uk/This podcast is part of the Podknows Podcasting ICN Network

Your AI tool isn't broken. It's just full.Hi, I'm Mike Fox, host of this podcast, "Lone Wolf Unleashed." I help solo founders systemise their businesses so they can switch off sooner and live larger. This week I'm pulling back the curtain on a real data project: 103,000 rows, a client locked into Microsoft Copilot, and a categorisation task that would've taken weeks to do manually.Here's what I worked through — and what you can take straight into your own business.The context window is the AI's working memory. Once it runs out, the quality of your outputs tanks — or the conversation just stops. Understanding this constraint is the difference between AI that saves you hours and AI that wastes them.Working within real-world limitations (not every client is on Claude), I built a strategy to break down a massive data set into token-efficient chunks, set up a structured workflow for Microsoft Copilot to process them in sequence, and then used a manager-agent review layer to QA the outputs before any human had to.The same principles apply whether you're running Claude, ChatGPT, or whatever tool your organisation has decided is the one. The constraints change. The framework doesn't.What you'll learn:What a context window is and why it limits what your AI can do with large data setsHow to make your data and your prompts token-efficient before you send themA practical chunking strategy for splitting large Excel or CSV files across multiple AI sessionsHow to use a manager-agent role to review and QA your AI outputsWhich model settings to use for heavy analytical tasksIf you're using AI to make decisions — not just write emails — this episode is for you.Resources, frameworks, and tools: lonewolfunleashed.com/resourcesMentioned in this episode:This podcast is part of the Podknows Podcasting ICN NetworkYou might also like...Check out the "Websites Made Simple" podcast with Holly Christie at https://websitesmadesimple.co.uk/

Running your own business shouldn’t feel like a never-ending marathon. If you’re clocking 60-hour weeks and dreaming about hiring your first employee just to claw back some sanity, this episode is for you. Hi, I'm Mike Fox, host of this podcast, "Lone Wolf Unleashed." In this episode I'm tackling the not-so-glamorous reality of delegation—why just deciding “I’ll get someone in to handle my marketing” won’t cut it, and why human beings bring as much risk as reward. Forget wishful thinking: you’ll learn why setting up solid processes, documenting your tasks (with templates to shave off real hours), and mapping out a hiring strategy are essential before posting a job ad or starting interviews.Timestamped summary:00:00 Setting up a hiring process04:57 Delegating tasks in your business09:46 Crafting interview questions and contracts13:21 Delegating your first hireMentioned in this episode:This podcast is part of the Podknows Podcasting ICN NetworkYou might also like...Check out the "Websites Made Simple" podcast with Holly Christie at https://websitesmadesimple.co.uk/

Most people building dashboards start in the wrong place. They worry about charts, colours, and layouts — when the real work happens long before any of that.Hi, I'm Mike Fox, host of this podcast, "Lone Wolf Unleashed." In this episode, I walk you through what actually needs to happen before a dashboard can tell you anything useful. Drawing on a real client scenario — a growing business moving from a file-based system to a CRM — I break down the data foundations you need in place first.We cover the sales pipeline as the most logical starting point, why tracking inquiry-to-answer time can expose problems you didn't know you had, and how a shorter sales cycle directly improves your cash flow. I also explain why starting manually — before you automate anything — is the right call, and how to keep your data ecosystem simple enough to actually maintain.If you've been thinking about dashboards, a new CRM, or just getting better visibility over what's happening in your business, this one lays the groundwork.📥 Resources and tools mentioned: lonewolfunleashed.com/resourcesTimestamped summary:0:00 — Why visuals are the last thing to worry about1:38 — Dashboards start with data2:29 — Sales pipeline metrics4:51 — Tracking DocuSign and sales cycle completion6:20 — Why you should start manually before automating7:30 — Connecting systems: APIs and AI agents9:00 — Keep your data ecosystem simple10:53 — Dashboard filters, date ranges, and wrap-up